Senior Machine Learning Engineer, Agent Oversight

About Scale

Scales mission is to develop reliable AI systems for the worlds most important decisions. As the leading AI data foundry we provide the high-quality data and full-stack technologies that power the worlds most advanced models fueling breakthroughs in generative AI defense and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust.

About the Team

Applied Intelligence Systems team is part of the Scale Generative AI Platform (SGP) focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production paired with applied ML research design and evaluation to ensure these systems perform reliably at the scale our customers demand. Were growing fast with increasing traction across both commercial and public sector customers and were just getting started this team will define what dependable production-grade agentic AI looks like.

About the Role

As a Machine Learning Engineer on Agent Oversight you will drive the end-to-end lifecycle that ensures our production agents perform reliably and improve over time. This includes building observability tools designing robust evaluation frameworks and developing improvement loops. Whether scaling infrastructure or researching new improvement methods you will navigate the entire ML loop while maintaining rigorous technical standards.

You will:

• Build or contribute to observability into agent behavior in production the signals and instrumentation needed to actually see what an agent is doing not just whether it succeeded or failed
• Design evaluation methodologies and metrics for agentic applications and work with the platform to make them run automatically at scale across different customer use cases not just as one-off analyses
• Build ship and own ML systems that detect drift anomalies or misalignment in production agent behavior from first prototype through running reliably at scale
• Design and run rigorous experiments to validate model and agent performance improvements before they ship
• Work alongside software engineers on the platform where your work intersects with broader infrastructure but youre expected to take your own work from idea to production not hand it off
• Collaborate closely with product managers customers data annotators Forward Deployed Engineers and other engineering teams to translate enterprise and government requirements into robust platform capabilities
• Depending on focus contribute to novel methods and approaches that push the state of the art for agent evaluation and improvement or focus on building ML systems that hold up reliably at scale in production

Requirements:

• 5 years of experience as an ML engineer or applied scientist ideally on a production ML or LLM-powered system not just consuming a third-party ML API within a feature
• Strong grounding inat least twoof the following:
  • Building or scaling evaluation monitoring or continuous-learning infrastructure for ML/agentic systems
  • Design experience for agent systems (architecture orchestration tool use)
  • Developing new methods reward models or model training/fine-tuning approaches
• Hands-on experience with LLMs and agent architectures tool use planning multi-agent orchestration
• Comfortable partnering with software engineers to productionize research and experimental work not just deliver a one-off analysis
• Rigorous approach to experimentation: clear hypotheses real statistical grounding and results that hold up under scrutiny
• Track record of collaborating across functions (Product Forward Deployed Engineering etc.) to navigate ambiguous requirements and bring them to production
• Gives direct substantive feedback on designs and code and takes it the same way and mentors others as they grow

Nice to have:

• Experience building or contributing to RLHF SFT or other fine-tuning/RL workflows reward modeling or verifiable-reward systems
• Experience with model or systems optimization (e.g. latency cost or inference efficiency)
• Published research open-source contributions or patents in agentic systems LLMs or applied ML
• Experience working in regulated or enterprise contexts
• Track record of taking a novel method from prototype to something running reliably in production navigating ambiguity along the way
• Experience reviewing others technical designs or mentoring engineers at a senior/staff level

PLEASE NOTE:Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale our mission is to develop reliable AI systems for the worlds most important decisions. Our products provide the high-quality data and full-stack technologies that power the worlds leading models and help enterprises and governments build deploy and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta Ernst & Young Mayo Clinic Time Inc. the Government of Qatar and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race color ancestry religion sex national origin sexual orientation age citizenship marital status disability status gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability please contact us at Please see the United States Department of Labors Know Your Rights poster for additional information.

We comply with the United States Department of Labors Pay Transparency provision.

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